Owing to inherent flexibility, compliant actuator with physical elastic elements can implement compliant interactions between robot and environment. Nonlinear stiffness elastic actuators (NSEAs) use one motor to adjust position and stiffness, which improve compactness of variable stiffness actuators, and consider high torque/force resolution and high bandwidth. The primary challenge of designing a NSEA is designing a reliable compliant mechanism with a given torque-deflection profile. In this study, a general design method of torsional compliant mechanism through given discrete torque-deflection points was proposed, where a chain algorithm based on 2R pseudo-rigid-body model was used to describe the large deformation in elastic elements. Moreover, the theoretical model of stiffness of a compliant mechanism based on series flexible beams was developed. Based on the proposed model, the dimensional parameters of proposed compliant mechanism were designed satisfying the condition of the given torque-deflection points. Finally, simulation and physical experiment of the designed compliant mechanism through three given torque-deflection points are conducted to show the effectiveness of the proposed method. The designed compliant mechanism was tested and evaluated in the self-developed NSEA.

In this paper, we propose a comparison of open-source LiDAR and Inertial Measurement Unit (IMU)-based Simultaneous Localization and Mapping (SLAM) approaches for 3D robotic mapping. The analyzed algorithms are often exploited in mobile robotics for autonomous navigation but have not been evaluated in terms of 3D reconstruction yet. Experimental tests are carried out using two different autonomous mobile platforms in three test cases, comprising both indoor and outdoor scenarios. The 3D models obtained with the different SLAM algorithms are then compared in terms of density, accuracy, and noise of the point clouds to analyze the performance of the evaluated approaches. The experimental results indicate the SLAM methods that are more suitable for 3D mapping in terms of the quality of the reconstruction and highlight the feasibility of mobile robotics in the field of autonomous mapping.

A 10 kV distribution network is critical for ensuring power supply to residents and factories. The number of power maintenance operations is rapidly increasing, and aerial cable stripping is a significant branch of these routine maintenances. High-voltage cable stripping, on the other hand, is mostly done manually, which is inefficient and poses serious security risks. As a result, this paper proposes an automatic wire stripping robot for use in a 10 kV power grid. The mechanical structure of the stripping robot is designed for installation on the insulating rod based on the working environment of 10 kV overhead cables. The robot was subjected to electromagnetic field simulation, modal analysis, and rigid-flexible coupling analysis. Finally, the robot prototype is built, and the PID controller is designed. Stripping tests are performed on a cable with a cross-sectional area of 95, 120, 150, 240, and 300 mm2, and the results are satisfactory.

This article presents a review of the platform configuration and dynamic of obstacle-surmounting unmanned ground vehicles (UGVs). For now, unmanned systems have emerged as a result of the rapid advancement of artificial intelligence and modern manufacturing techniques both domestically and internationally. The research on unmanned systems has been improved a lot. The UGV platform can execute transportation, recurring, and military tasks independently. For the high-level self-control, adaption, and maneuverability abilities, the UGV platform has been applied in the military, industry, and other special fields widely. The UGV platform usually performs tasks in an unstructured environment, so the all-terrain performance becomes a key factor restricting their operating efficiency and reliability. A brief literature review of the UGV platform is carried out in this article.

This paper presents a low-cost, accurate indoor positioning system that integrates image acquisition and processing and data-driven modeling algorithms for robotics research and education. Multiple overhead cameras are used to obtain normalized image coordinates of ArUco markers, and a new procedure is developed to convert them to the camera coordinate frame. Various data-driven models are proposed to establish a mapping relationship between the camera and the world coordinates. One hundred fifty data pairs in the camera and world coordinates are generated by measuring the ArUco marker at different locations and then used to train and test the data-driven models. With the model, the world coordinate values of the ArUco marker and its robot carrier can be determined in real time. Through comparison, it is found that a straightforward polynomial regression outperforms the other methods and achieves a positioning accuracy of about 1.5 cm. Experiments are also carried out to evaluate its feasibility for use in robot control. The developed system (both hardware and algorithms) is shared as an open source and is anticipated to contribute to robotic studies and education in resource-limited environments and underdeveloped regions.

The analytical expression of driving force is helpful to quickly plan the kinematic trajectory of parallel mechanism for automatic drilling and riveting. For parallel posture alignment mechanism, because of its closed-loop characteristics, the inverse dynamic solution is more complex, especially for parallel bracket with actuation redundancy. Considering that the telescopic rods are actually flexible parts, the dynamic analytical modeling is carried out with deformation supplementary equation. Taking the force at the spherical joint as the intermediate variable and the driving force of each active prismatic pair are analytically analyzed by vector cross-product. The modeling was verified by experiment. Compared with previous research methods, the analytical method proposed improves the solution accuracy of driving force slightly and reduces the driving force solution time by 56.28%, which is high efficiency. The maximum error percentage is 1.61%, and the experimental results show that the method of inverse dynamics modeling is practical. This paper can be used for driving force analysis of parallel posture alignment mechanism based on positioner in the field of aircraft assembly.

Driven by the remarkable developments we have observed in recent years, path planning for mobile robots is a difficult part of robot navigation. Artificial intelligence applied to mobile robotics is also a distinct challenge; reinforcement learning (RL) is one of the most used algorithms in robotics. The exploration-exploitation dilemma is a motivating challenge for the performance of RL algorithms. The problem is balancing exploitation and exploration, as too much exploration leads to a decrease in cumulative reward, while too much exploitation locks the agent in a local optimum. This paper proposes a new path planning method for mobile robot based on Q-learning with an improved exploration strategy. In addition, a comparative study of Boltzmann distribution and $\epsilon$-greedy politics is presented. Through simulations, the better performance of the proposed method in terms of execution time, path length, and cost function is confirmed.

Devices known as kinematic couplings offer accurate, repeatable, and stiff connections between two parts. They are characterized by point contacts and enable great repeatability with errors less than 1 micron, in contrast to conventional coupling systems like alignment pins or those based on elastic deformation. In this study, a robotized laser-cutting machine is equipped with a three-groove kinematic coupling design to increase the precision of workpiece placement. Given the application’s requirements, a preliminary design of the coupling is defined. An analytical approach is provided for calculating stresses and deflections at the locations where balls and grooves make contact, and it is then utilized to calculate positioning errors caused by the mechanical structure’s elastic deformation under various loading conditions. The outcomes of the simulations are finally discussed and highlight the efficacy of the solution tested.

A novel couple-constrained parallel wrist with three measuring force flexible fingers is designed for grabbing heavy objects and measuring grabbed forces. Its prototype is developed, its dynamics model is established, and its grabbing forces are measured. First, using the extended formulas of the skew-symmetric matrix, the kinematic formulas are derived for solving the Jacobian/Hessian matrices and the general velocity/acceleration of the moving links in the couple-constrained parallel wrist. Second, a dynamics model is established for solving the dynamic actuation forces, the couple-constrained forces, and the torque in the couple-constrained parallel wrist. Third, the theoretical solutions of the kinematics/dynamics of the couple-constrained parallel wrist are verified using a simulation mechanism. Finally, the grabbing forces of the three flexible fingers are measured and analyzed.

As a heavy load is applied to the parallel manipulators, it causes inaccuracies while positioning the end-effector or unbalanced dynamic forces in the legs. Various load-balancing techniques overcome this. However, the disadvantage of most load-balancing mechanisms is that they add inertia to the assembly and decrease the speed of motion. This article studies a new load-balancing method (a passive damper mechanism). The passive balancing mechanism is proposed to negate the inertia effects while countering the static inaccuracies in the parallel mechanism. This is verified by the structural analysis of the mechanism. The impact of the damper element on the dynamics of the mechanism is unknown. Hence, a complete mathematical model for the balancing mechanism has been developed to study its impact on the dynamics of the entire structure. Laplace transformations characterize the system response. The inclusion of a passive damper in a 3-prismatic-prismatic-revolute-spherical system was examined and found to be stable and critically damped. Such a passive damper was envisaged to facilitate additional force transmission for the actuators, and the DC gain from the system response validates the torque support for the actuators.

Collective decision-making by a swarm of robots is of paramount importance. In particular, the problem of collective perception wherein a swarm of robots aims to achieve consensus on the prevalent feature in the environment. Recently, this problem has been formulated as a discrete collective estimation scenario to estimate their proportion rather than deciding about the prevalent one. Nevertheless, the performance of the existing strategies to resolve this scenario is either poor or depends on higher communication bandwidth. In this work, we propose a novel decision-making strategy based on maximum likelihood estimate sharing (MLES) to resolve the discrete collective estimation scenario. Experimentally, we compare the tradeoff speed versus accuracy of MLES with state-of-the-art methods in the literature, such as direct comparison (DC) and distributed Bayesian belief sharing (DBBS). Interestingly, MLES achieves an accurate consensus nearly 20% faster than DBBS, its communication bandwidth requirement is the same as DC but six times less than DBBS, and its computational complexity is $O(1)$. Furthermore, we investigate how noisy sensors affect the effectiveness of the strategies under consideration, with MLES showing better sustainability.

Bending and elongation have been some of the most studied motions in soft actuators due to the variety of their applications. For that matter, multi-DOF actuators have been developed with the purpose to generate different movements in a single actuator, mainly bending.

However, these actuators are still limited in mobility range, and some of them do not perform continuous curvatures. This paper presents the design, characterisation and implementations of a multi-DOF soft pneumatic module. The internal structure of the proposed module is composed of four channels, which generate bending in several directions. The finite element method analysis demonstrates that the actuator performs continuous curvatures for different pressure values. We present a repeatable and easy manufacturing process using the casting technique, considering the material Ecoflex 00-50; as well as the kinematic model of the actuator, taking into consideration two bending Degrees of Freedom (DOFs). Furthermore, we performed bending characterisation for all possible combinations of the four channels via computer vision, demonstrating a wide mobility range and performing continuous curvatures. Additionally, we evaluated the kinematic model with characterisation data, obtaining the angular and cartesian relationship between the pressure and continuous curvatures. On the other hand, the authors propose the design of a modular soft manipulator based on two multi-DOF modules. The kinematic model is reported. In addition, we implement a motion sequence in the manipulator to pick and place tasks.

Stereo vision allows machines to perceive their surroundings, with plane identification serving as a crucial aspect of perception. The accuracy of identification constrains the applicability of stereo systems. Some stereo vision cameras are cost-effective, compact, and user-friendly, resulting in widespread use in engineering applications. However, identification errors limit their effectiveness in quantitative scenarios. While certain calibration methods enhance identification accuracy using camera distortion models, they rely on specific models tailored to a camera’s unique structure. This article presents a calibration method that is not dependent on any particular distortion model, capable of correcting plane position and orientation identified by any algorithm, provided that the identification error is biased. A high-precision mechanical calibration platform is designed to acquire accurate calibration data while using the same detected material in real measurement scenarios. Experimental comparisons confirm the efficacy of plane pose correction on PCL-RANSAC, with the average relative error of distance reduced by 5.4 times and the average absolute error of angle decreasing by 41.2%.

Wearable robots, sometimes known as exoskeletons, are incredible devices for improving human strength, reducing fatigue, and restoring impaired mobility. The control of powered exoskeletons, on the other hand, is still a challenge. This necessitates the development of a technique to simulate exoskeleton–wearer interaction. This study uses a two-dimensional human skeletal model with a powered knee exoskeleton to predict the optimal lifting motion and assistive torque. For lifting motion prediction, an inverse dynamics optimization formulation is utilized. In addition, the electromechanical dynamics of the exoskeleton DC motor are modeled in the lifting optimization formulation. The design variables are human joint angle profiles and exoskeleton motor current profiles. The human joint torque square is minimized subject to physical and lifting task constraints. Then, the lifting optimization problem is solved by the gradient-based sparse nonlinear optimizer (SNOPT). Furthermore, the optimal exoskeleton torque is implemented through a two-phase control strategy to provide optimal assistance in lifting. Experimental validations of the optimal control with 6 Nm and 16 Nm maximum assistive torque are presented. Both 6 Nm and 16 Nm maximum optimal assistance of the exoskeletons reduce the mean values of vastus lateralis, biceps femoris, and latissimus dorsi muscle activations compared to the lifting without the exoskeleton. However, the mean value of the vastus medialis activation is increased by a small amount for the exoskeleton case, although its peak value is reduced. Finally, the experimental results demonstrate that the proposed lifting optimization formulation and control strategy are promising for powered knee exoskeleton for lifting tasks.

This paper focuses on the design, analysis, and multi-objective optimization of a novel 5-degrees of freedom (DOF) double-driven parallel mechanism. A novel 5-DOF parallel mechanism with two double-driven branch chains is proposed, which can serve as a machine tool. By installing two actuators on one branch chain, the proposed parallel mechanism can achieve 5-DOF of the moving platform with only three branch chains. Afterwards, analytical solution for inverse kinematics is derived. The 5$\times$5 homogeneous Jacobian matrix is obtained by transforming actuator velocities into linear velocities at three points on the moving platform. Meanwhile, the workspace, dexterity, and volume are analyzed based on the kinematic model. Ultimately, a stage-by-stage Pareto optimization method is proposed to solve the multi-objective optimization problem of this parallel mechanism. The optimization results show that the workspace, compactness, and dexterity of this mechanism can be improved efficiently.

This paper proposed an elastodynamic modeling method combined with independent displacement coordinates and substructure synthesis technology. Firstly, the connecting rod was discretized, and the elastodynamic control equation for each element was established. The multipoint constraint element theory, linear algebra, and singularity analysis were used to identify the globally independent displacement coordinates of the manipulator. On this basis, the elastodynamic model using the substructure synthesis for the 3-PRS parallel manipulator (PM) was developed, with its natural frequencies distribution in the regular workspace discussed. The comparison with the finite-element results showed that the maximum error of the first three-order natural frequencies was within 1.03%, which verified the correctness of the analytical model. The proposed elastodynamic model included all the kinematic constraints of the manipulator without increasing the Lagrangian multiplier. The method is computationally efficient and assesses the dynamic behaviors of the mechanism at the predesign phase.

It is very challenging for robots to perform grinding and polishing tasks on surfaces with unknown geometry. Most existing methods solve this problem by modeling the relationship between the force sensing information and surface normal vectors by analyzing the forces on special end tools such as spherical tools and cylindrical tools and simplified friction model. In this paper, we propose a normal vectors learning method to simultaneously control end-effector force and direction on unknown surfaces. First, the relation that mapping the force sensing information to the surface normal vectors is learned from the demonstrated data on the known plane using locally weighted regression. Next, the learned relation is used to estimate surface normal vectors on the unknown surface. To improve the force control precision on the unknown geometry surface, the adaptive force control is developed. To improve the direction control precision due to friction, the iterative learning control is developed. The proposed method is verified by comparative simulations and experiments using the Franka robot. Results show that the end-effector can be controlled perpendicular to the surface with a certain force.

The axial offset joint has two rotating axes that do not intersect but have a specific offset in space. It is used widely in parallel manipulators (PMs). The offset-joint workspace can directly affect the PM workspace. This study performed a theoretical derivation and workspace analysis of a class of axial offset joints. First, a theoretical parametric model describing the rotation range of the offset joint is established that considers the interference of the offset joint because of the contact between the upper- and lower-joint brackets during movement. Second, the analytical expressions of the offset-joint workspace are formulated based on the coordinate system transformation. The offset-joint workspace is theoretically calculated in this study using formulations. Then, through a comparative analysis, the superiority of the offset joint compared with the universal joint is verified. The theoretical formulations in this paper can be used to calculate the workspace of a class of axial offset joints. Finally, based on a workspace analysis of three types of PMs using offset, universal, and spherical joints, the offset-joint PM workspace is much larger than those of the other two types.